Role of Polymorphisms in MicroRNA-196a2, MicroRNA-499 and MicroRNA-146a for Prostate and Gastric Cancer Risk: An Updated Meta-analysis

Maheen Zahra¹ | Saman | Rauf Ramay¹ | Haseeb Nisar¹* | Mubbasher Munir² | Anum Javaid³ | Muhammad Khurram¹ | Samiah Shahid⁴ | Wardah Nisar⁵ | Komal Javed¹

1. INTRODUCTION

MicroRNAs (miRNAs) are small 17-25 non-coding nucleotides that play a significant role in gene expression regulation and controlling various physiological developments including many cellular processes, proliferation, differentiation, and apoptosis. They undergo their function by repressing translational mechanisms or degrading mRNA by binding to the 3´-untranslated region (3´-UTR) of target mRNAs [1][2][3]. The role of single nucleotide polymorphisms (SNPs), which are the most common type of mutations found in the human genome, within these miRNAs have been instrumental in altering these biological mechanisms controlled by these small nucleotides resulting in progression of various types of cancers [4][5][6].

The function of miRNAs that regulate genes essential for prostate cell growth and survival can be impacted by certain polymorphisms. For instance, variations in miRNAs that target genes such as the androgen receptor (AR) or prostate-specific antigen (PSA) might affect androgen signaling pathways, which in turn can accelerate the development of prostate cancer. Apoptosis avoidance, unchecked cell proliferation, and the advancement of cancer are all possible outcomes of disruptions in the regulation of miRNA. Similar to this, polymorphisms in GC can impact miRNAs that control genes related to inflammation, gastric mucosal integrity, and the body's reaction to Helicobacter pylori infection, a key risk factor for GC. Epithelial-mesenchymal transition (EMT), metastasis, and chronic inflammation can all be influenced by polymorphisms in miRNAs, including miR-146a, miR-196a2, and miR-499. These polymorphisms might result in altered expression or function. The development and progression of gastric cancer can be impacted by these alterations in oncogenes and tumor suppressors (e.g., KRAS, PIK3CA, TP53).

Recently studies have reported the most frequent SNPs in these miRNAs to be associated with Prostate (PCa) and Gastric Cancer (GC). Some of these notable SNPs include rs2910164 C>G present in miR-146a, rs11614913 C>T located in miR-196a2, and rs37346444 A>G present in miR499 have been extensively studied in cancer risk and its susceptibility [7][8][9][10][11]. Although role of these SNPs have been studied in relation with possible association with cancer, nevertheless the results have been variable. For instance, Zhou et al. found a significant role of rs37346444 A>G in progression of cervical squamous cell carcinoma while Tian et al. and Srivastava et al. have failed to find a possible role of this SNP in lung and gall-bladder cancer respectively [12][13]. Similarly, some researchers have revealed the role of minor allele C in rs2910164 in reducing the PCa cancer (PCa) risk in the Chinese Han population [14] while others have reported no significant evidence of this variant in PCa development in other populations [15]. The reason behind this substantial inconsistency in the SNPs data may be due to different ethnic backgrounds, varied sample sizes, and the corrected physiological status [16, 17].

One of the strategies for resolving these inconsistencies in these reported studies is to undergo a more precise statistical analysis. Meta-analysis provides a more logical methodology for removing these heterogeneities by combining, summarizing, and critically analyzing the previous research work conducted across different sample sizes and ethnic communities. We conducted an up-to-date meta-analysis on all available case-control studies by combining data to achieve a bigger sample and increasing the statistical power to assess the relationship between miRNAs and cancer risk.

2. MATERIALS AND METHODOLOGY

2.1 Literature Search for Identification of Eligible Studies and Data Extraction

The meta-analysis was performed according to the guidelines of Preferred Reporting Items for Meta-analyses (PRISMA) [18]. Two authors (Zahra M. and Ramay S.R) performed an extensive literature review using PubMed, Springer-Link, and Google Scholar as databases up to October 21^st, 2022 with the following keywords: “miR-146a”, “miR-196a2”, “miR499”, “Prostate cancer”, “Gastric cancer” and “polymorphism”. We assessed relevant articles by evaluating their titles and abstracts for inclusion in our meta-analysis. Studies including review articles, comments, meta-analysis, and data from family-based linkage analysis and/or overlapping data were eliminated. The studies suitable for our analysis met with certain inclusion criteria: (a) original case-control studies with odds ratios (ORs), 95% confidence intervals (CIs), and mentioned p values, (b) articles published in English, (c) accessibility of genotypes and allele frequencies from each relevant article.

Similar articles present in different databases were removed to avoid repetition. Each article that met our inclusion criteria was scrutinized independently by two reviewers. The information extracted from each study were included: the author's name, year of publication, ethnicity, genotyping method, the sample size in both case and control categories, genotype, and allelic frequencies.

2.2 Statistical Analysis

The strength of the association between rs2910164, rs11614913, and rs37346444 and PCa and GC was analyzed by the ORs and their corresponding 95%CI. We used four genetic models (allelic, wild-type homozygote, recessive allele homozygote, and heterozygous) to obtain the pooled ORs. Additionally, stratified subgroup analysis was performed by ethnicity (Asian or Caucasian). Chi-squared based Q statistic test (To evaluate whether a difference between two categorical variables is the result of chance or a relationship between them, the Chi-Square test is a statistical procedure that can be used to determine the difference between observed and expected data) was used to identify differences between studies [19]. Using the I² statistic test (It indicates the percentage of variation in the observed effect that results from variation in the genuine effects as opposed to sampling error), the impact of heterogeneity was calculated and classified as high (I² > 50%), moderate (25% I² 50%), and low (I² 25%). The I² statistic test was performed to assess the impact of heterogeneity that was classified as high (I² > 50%), moderate (25% I² 50%), and low (I² 25%) [20]. Results with p-value< 0.10 and an I²> 50%, indicates high level of heterogeneity, thereby applying random effect model. Alternatively, when there was no heterogeneity, a fixed effect model was used. To ascertain whether publication bias existed, funnel plots and Egger's linear regression tests were performed [21]. A two-sided p-value <0.05 was considered as statistically significant. All the analyses were performed by using STATA software version 14.1 (USA).

3. RESULTS

3.1 Study Characteristics

The main characteristics of selected studies investigating the association of miR-196a2 rs11614913, miR-146a rs2910164, and miR-499 rs3746444 with PCa and GC are shown in Table 1 and Table 3. There were 4611 articles relevant to searching words found in PubMed and Google Scholar.  1812 were excluded because they were meta-analysis and comments. After performing an in-depth analysis of selecting relevant studies using the inclusion and exclusion criteria, a total of 54 articles were included in our study. In total, 27 articles were enrolled in the current study after removing duplicates and studies that do not include SNPs related to our analysis. A flow chart of studies selected using PRISMA guidelines is indicated in Figure 1.

Figure 1. PRISMA Chart showing the approach adopted during the literature search among the associated studies

Table 1. Characteristics of all studies related to PCa Cancer in the meta-analysis

Abbreviations: PCR-RFLP (Polymerase chain reaction-restriction fragment length polymorphism), T-ARMS-PCR (tetra-primer amplification refractory mutation system polymerase chain reaction, HRMA (High resolution melt analysis)

Table 2. Total and stratified group analysis according to ethnicity for the three miRNAs polymorphisms and PCa susceptibility

Abbreviations: F (Fixed effect model), R (Random effect model)

Figure 2. Meta-analysis of the relationship between miR-196a2 rs11614913 C>T polymorphism and prostate cancer risk for different regions. A) (Heterozygous Asian Model); B) T allele Asian Model; C) Allele C Overall Model; D) Allele C Asian Model

Table 3. Characteristics of all studies related to GC in the meta-analysis

Figure 3. Meta-analysis of the relationship between miR-499 rs3746444 A>C polymorphism and gastric cancer risk for different regions. A) Allele C Overall Model; B) Allele C Asian Model

Table 4. Total and stratified group analysis according to ethnicity for the three miRNAs polymorphisms and GC susceptibility

Abbreviations: F (Fixed effect model), R (Random effect model)

Figure 4. Begg’s funnel plot for publication bias of miR-196a2 rs11614913 polymorphism and prostate cancer risk. A) T allelic overall model; 4B) T allelic Asian model; 4C) C allelic overall model; 4D) C allelic Asian model; 4E) C allelic overall model; 4F) C allelic Asian model. *Each point represents a separate study for the indicated association. Logor represents the natural logarithm of OR. The horizontal line means the magnitude of the effect. A funnel plot with pseudo 95% confidence limits was used

3.2 Association between miR-196A2, miR-146a and miR-499 Polymorphism and PCa

For PCa cancer, a total of seven studies were included with samples ranging from 100-355. There were 5 studies from Asian ethnicity and 2 studies from European ethnicity. Controls in each study were age and gender-related to cases. Results from the study showed that miR-196a2 rs11614913 C>T polymorphism might be associated with PCa susceptibility in two genetic models. The estimated allele model in the Asian population (CvsT: OR=1.207, 95%CI: 1.023-1.425, P=0.026) and heterozygous model in the Asian population (CvsT: OR=1.264, 95%CI: 1.008-1.585, P=0.042) were significantly associated with PCa. The miR-146a SNP rs2910164 C>G didn’t show any significant association with any genetic models while the miR499 rs3746444 A>C showed significant association in the allele model in the overall population (AvsC: OR=1.201, 95%CI: 1.039 -1.388, P=0.013) and also in Asian subjects (AvsC OR=1.23, 95%CI: 1.030-1.469, P=0.022) (Table 2 and Figure 2). Association between miR-196A2, miR-146a and miR-499 polymorphism and GC.

For GC, total 20 studies were included with sample ranging from 142-1895. There were 16 studies from Asian ethnicity and 4 studies from European ethnicity (Table 4). Controls in each study were age and gender-related to cases. Results from the study showed miR-499 rs3746444 A>C polymorphism might be associated with increased GC susceptibility in all four genetic models i.e. allele model P=0.228, dominant model P=0.002, heterozygote model P=0.02, recessive model P=0.028. In the subgroup analysis for ethnicity, a significant association between miR-499 rs3746444 A>C and risk of GC was found in Asian subjects in all genetic models i.e. allele model P=0.000, dominant model P=0.001, heterozygote model P=0.030, recessive model P=0.009. The miR-196a2 rs11614913 C>T and miR-146a SNP rs2910164 C>G didn’t show any significant association with any genetic models in the overall study and subgroup analysis according to ethnicity (Table 4 and Figure 3) Evaluation of Publication Bias

In order to access the publication bias of literature, we used Begg’s funnel plot (Figure 4) and Eggers test. The shape of the funnel plots did not reveal any evidence of obvious asymmetry for all genetic models in the overall meta-analysis. Egger’s test was used to provide statistical evidence of funnel plot asymmetry. Egger’s test only detected evidence of publication bias in the subgroup analysis of European subjects in prostate and gastric cancer for all genetic models (P<0.05). However, Egger’s test was not applied in some comparisons due to the small number of studies.

4. DISCUSSION

The role of SNPs in cancer susceptibility is the most studied type of human genetic variation due to advancements in screening technologies. Efforts to understand the role of SNPs present in precursor and mature miRNA and their effects on the progression of various diseases have been an area of interest. Researchers have shown that SNPs in miRNA precursor and mature miRNA may influence the process of gene coding and splicing, affecting different types of cancer susceptibility. Through modifying the primary transcript of miRNA processing, maturation, and miRNA-miRNA interaction, these alterations also affect cancer susceptibility and play a significant role in the development of primary and metastatic cancers [22][23]24]. Thus it is important to find the association between miRNA SNPs and cancer to further explicate the mechanisms of carcinogenesis. Even though numerous studies have been published on the association of miR-196a2 rs11614913, miR-146a rs2910164, and miR499 rs3746444 polymorphism and cancer risk, the results have been heterogynous that might be due to small sample size and differences in cancer type and ethnicities. Therefore, to achieve a uniform conclusion and a more precise assessment of the relationship, we performed this meta-analysis. The current study is an updated meta-analysis of the association between miR-196a2, miR-146a and miR-499 polymorphisms and the risk of PCa and GC. New case control studies from recent years were included in the current investigation, and some new conclusions have been suggested.

The results from our study have demonstrated that the minor allele in miR-499 rs3746444 T→C might contribute to PCa in overall study while minor allele variant in miR-196a2 rs11614913 C→T might be involved in increasing the risk for PCa in Asian population. The results from GC have shown that miR-499 rs3746444 T→C were significantly associated in all genetic models being studied in overall and Asian subjects when stratified by ethnicity. The miR-196a2 gene produces two unique mature miRNAs (miR-196a-3P and miR-196a-5P), which are processed from the same precursor miRNA [25], its varied expression patterns may have an impact on the miR-196a's possible targets. The processing or target selection of miRNAs [26, 27], which is known to be a major factor in oncogenesis and helps to control the translation or breakdown of messenger RNA, may be affected by SNPs in miRNA genes (mRNA) [28]. Previous meta-analysis being published to determine the correlation between rs3746444 and the risk of GC didn’t find any significant association that might be due to limited studies [17, 29-33]. More than 150 genetic association studies have been conducted to examine the relationship between the human miR-196a2 rs11614913 variant and susceptibility to various cancers; however, these research have produced conflicting results. To elucidate a more definite role and examine the role of rs11614913 of miR-196a2 that is linked to the likelihood of developing cancer, several meta-analyses have been carried out in the past [34][35]. It should be noted that these meta-analyses also lacked certain promising and recent studies that need to be taken into account to determine the exact relationship between this variation and cancer susceptibility. In order to produce a concrete result, we thus carried out this meta-analysis, incorporating the greatest number of association studies carried out in various cohorts or races.

Despite the fact that this study combined all previous research and examined the relationship between rs11614913, rs2910164 and rs3746444 with PCa and GC development, some limitations also need to be addressed. Firstly, although we rigorously checked the papers and carefully retrieved the data, the variations in the subject selection could not be completely removed. Secondly we only include Asian and Caucasian ethnicities in our sub group analysis and the influence of differences in racial descent should not be avoided. Thirdly, studies from languages other than English were excluded, thus including potential language biasness. Fourthly, it could be beneficial to confirm our findings with a different cohort. However, a cohort analysis was not carried out because there were insufficient data. Finally, despite the fact that we find the connection between rs11614913, rs3746444, and the establishment of PCa and GC, the purpose and mechanism of this polymorphism remained a mystery.

In conclusion, polymorphisms in the miR-196a2 rs11614913 and miR-499 rs3746444 may have a role in the onset of PCa and GC. It may be helpful as a candidate marker for the diagnosis of various diseases and may potentially increase the risk of developing cancer in Asian population. Additionally, larger-scale research and investigations focusing on specific cancer types or ethnicities should be conducted to confirm the findings.

Acknowledgements: Authors are grateful to Department of Life-Sciences, University of Management and Technology for providing facilities and support in this research.

Author Contributions: MZ and SRR do the analysis and write up, HN supervise the whole project and write up of the manuscript, MM provide valuable inputs regarding statistical analysis and interpretation, AJ, MK, SS provide assistance in data analysis and proof reading, WN help in data collection and literature review

Conflict of Interest Statement: Authors declare no potential conflicts of interest in this manuscript.

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